What is PRD-driven AI coding?
It is using a product requirements document to define scope, constraints, stories, acceptance criteria, and review expectations before an AI coding agent edits files.
Glossary
PRD-driven AI coding uses a product requirements document to guide agent planning, story splitting, implementation, and review.
Why it matters
PRD-driven AI coding gives an agent a product target and gives the developer a source document for review.
PRD-driven AI coding means using a product requirements document to guide an AI coding agent from scope to implementation review. The PRD defines the user, behavior, constraints, acceptance criteria, and non-goals before the agent starts changing files.
A developer writes or generates a PRD, reviews the scope, splits the work into smaller stories, and validates those stories before implementation. The agent then works against a more explicit target than a one-line prompt.
In Hal, the workflow can look like this:
hal plan "describe the product change"
hal convert
hal validate
hal runAI coding agents are sensitive to ambiguity. If the prompt does not define success, the agent may invent scope or optimize for the wrong outcome. A PRD gives both the agent and the reviewer a shared source of truth.
| Dimension | PRD-driven AI coding | Direct agent prompting |
|---|---|---|
| Scope | Written before implementation. | Often negotiated during the chat. |
| Review | Compared against requirements and criteria. | Compared against the latest conversation. |
| Risk control | Encourages story splitting and validation. | Easy to over-broaden. |
| Best fit | Product changes with behavior and edge cases. | Tiny edits or exploratory work. |
Hal is built around PRD-native coding loops. It helps move from product intent into planned, validated, reviewable work while still requiring a developer to inspect generated output before merging.
Check the current Hal repository, install docs, and release notes before relying on command behavior in production work.
Short answers before you put this into an agent workflow.
It is using a product requirements document to define scope, constraints, stories, acceptance criteria, and review expectations before an AI coding agent edits files.
No. It is most useful when a change has product behavior, edge cases, or review risk that should be written down before implementation.
Keep exploring the pieces of a reviewable coding loop.
PRD-native development means using a product requirements document as the source of truth for planning, implementation, and review.
An AI coding loop is a repeated plan, implement, inspect, and continue workflow for agent-assisted software development.
Acceptance criteria define observable conditions a story must satisfy before generated code can be accepted after review.